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This book explores recent advances in uncertainty quantification for hyperbolic, kinetic, and related problems. The contributions address a range of different aspects, including: polynomial chaos expansions, perturbation methods, multi-level Monte Carlo methods, importance sampling, and moment methods. The interest in these topics is rapidly growing, as their applications have now expanded to many areas in engineering, physics, biology and the social sciences. Accordingly, the book provides the scientific community with a topical overview of the latest research efforts.

Uncertainty (Information theory) --- Mathematics. --- Partial differential equations. --- Computer mathematics. --- Social sciences. --- Partial Differential Equations. --- Computational Mathematics and Numerical Analysis. --- Mathematical and Computational Engineering. --- Numerical and Computational Physics, Simulation. --- Mathematics in the Humanities and Social Sciences. --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Partial differential equations --- Math --- Science --- Mathematics --- Measure of uncertainty (Information theory) --- Shannon's measure of uncertainty --- System uncertainty --- Information measurement --- Probabilities --- Questions and answers --- Differential equations, partial. --- Computer science --- Engineering mathematics. --- Engineering --- Engineering analysis --- Mathematical analysis --- Applied mathematics. --- Physics. --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics

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This book tackles important problems of anomaly detection and health status analysis in complex core router systems, integral to today’s Internet Protocol (IP) networks. The techniques described provide the first comprehensive set of data-driven resiliency solutions for core router systems. The authors present an anomaly detector for core router systems using correlation-based time series analysis, which monitors a set of features of a complex core router system. They also describe the design of a changepoint-based anomaly detector such that anomaly detection can be adaptive to changes in the statistical features of data streams. The presentation also includes a symbol-based health status analyzer that first encodes, as a symbol sequence, the long-term complex time series collected from a number of core routers, and then utilizes the symbol sequence for health analysis. Finally, the authors describe an iterative, self-learning procedure for assessing the health status. Enables Accurate Anomaly Detection Using Correlation-Based Time-Series Analysis; Presents the design of a changepoint-based anomaly detector; Includes Hierarchical Symbol-based Health-Status Analysis; Describes an iterative, self-learning procedure for assessing the health status.

Routing (Computer network management) --- Computer networks --- Management --- Electronic circuits. --- Computer engineering. --- Internet of things. --- Embedded computer systems. --- Electrical engineering. --- Circuits and Systems. --- Cyber-physical systems, IoT. --- Communications Engineering, Networks. --- IoT (Computer networks) --- Things, Internet of --- Embedded Internet devices --- Machine-to-machine communications --- Computers --- Electric engineering --- Engineering --- Embedded systems (Computer systems) --- Computer systems --- Architecture Analysis and Design Language --- Electron-tube circuits --- Electric circuits --- Electron tubes --- Electronics --- Design and construction